1. Technical Field
The present invention relates to data streaming systems and more particularly to a system and method for improving content diversification using source pushed data without building a tree.
2. Description of the Related Art
Multimedia content delivery using peer-to-peer (P2P) technology has proven to have a scalability advantage over a traditional client/server or content delivery network (CDN) infrastructure-based delivery model. Popular applications include bitTorrent, PPLive, Coolstreaming, etc.
Data driven P2P networks include a basic bitTorrent protocol model. In a data driven P2P network, nodes connect to each other to form a random mesh. A node pulls chunks of content from its neighbors until the complete multimedia content replica is obtained.
Data driven P2P swarming will now be described. A joining node first contacts a bootstrapping node, usually a tracker or the content source, to obtain a list of existing peers of a session. The joining node then tries to establish a connection with a subset of nodes on the list. Neighboring nodes exchange a buffer map (BM) to announce their local content availability. Based on this information, a node can pull missing chunks from the corresponding neighbors.
Content diversity is the difference in locally buffered content between a node and its neighbor. For example, if a node has chunks 1 and 3, and its neighbor also has chunks 1 and 3, then there is nothing new they can exchange. However, if the node's neighbor has chunks 2 and 4, then the upload bandwidth of the both nodes can be utilized for uploading the missing chunks to each other. The higher the content diversity, the more upload bandwidth can be utilized. This leads to better P2P streaming performance in terms of higher streaming rate or lower delay and latency.
There are several existing methods to improve content diversity in data driven P2P streaming systems. “Rarest First” is a pull based method. Nodes pull rarest chunks in their neighborhood first. While this improves content diversity, the success of this method depends on the pulling node's BM information accuracy. Periodically, out-dated BM information makes the “Rarest” chunks get downloaded multiple times from the same source in the neighborhood. This decreases the potential for more efficient content swarming.
Recently, a new method for improving content diversity has been proposed. A source divides the content into sub-streams, say sub-stream 1 has chunks 1, 3, 5, . . . and sub-stream 2 has chunks 2, 4, 6, . . . , etc. Peers subscribe to sub-streams by picking a suitable parent to receive the feed. The source pushes each sub-stream to a corresponding subscribing tree. Peers receiving different sub-streams differ greatly in their content, thus achieving a high content diversity. Trees are also built to force different content to flow through different sets of peers with the purpose for improving content diversity.
The weakness of all these methods is the reduced robustness against system churn due to the fact that distribution trees are needed. In practice, building and maintaining trees contributes to system fluctuation especially during high churn when users frequently join and leave.